[1]} exploited the shortest dependency path (SDP) between two entities and the sub-trees attached to that path (augmented dependency path) for relation extraction. Each token in the SDP is represented using its pre-trained embedding and its sub-tree representation. The sub-tree representation of a token is obtained from the sub-tree of the dependency tree where the token is the root node. The dependency relations are represented using trainable embeddings. Each node in the sub-tree of a token receives information from its children including the dependency relations. The sub-tree representation of the token is obtained by following the sub-tree rooted at the token from its leaf nodes to the root in a bottom-up fashion. Next, they use CNN with max-pooling on the vectors of the sequence of the tokens and dependency relations across the SDP. The output of the max-pooling operation is passed to a classifier to find the relation.
